Robust frequency offset estimation with a single symbol for FH-OFDMA

Efficient carrier frequency offset estimation algorithm for generalized frequency division multiplexing systems

In this paper, we propose a new carrier frequency offset (CFO) estimation algorithm and a new CFO correction structure in the multi-stage synchronization strategy in time and frequency domain for OFDM. The new CFO estimation algorithm uses all pilots including continual pilots (CP) and scattered pilots (SP) to estimate the CFO in frequency domain, and it can acquire more accurate estimation results than the conventional algorithm only using CP. The new CFO correction structure is a double-loop structure, and in the double-loop synchronization structure, fractional frequency offset (FFO) is corrected using a long loop as conventional method, however, integral frequency offset (IFO) does not go back to the time domain, and it is recovered using a short loop in frequency domain, which can shorten the convergence time of frequency synchronization. The analysis and simulations show the improved performance of the proposed CFO estimation algorithm and the double-loop correction structure.

In this paper, we propose a low-complexity carrier frequency offset (CFO) estimation algorithm for OFDM based wireless LAN, IEEE 802.11a. The complexity of the arctangent operation to calculate the argument of auto-correlation for CFO estimation is reduced by a novel range pointer method. The proposed algorithm estimates fine CFO value first and then based on the fine CFO value, simple criteria is used for the boundary decision of integer CFO estimation. The simulation results show that the performance of the proposed algorithm is slightly better than the conventional method while the computational complexity is reduced by 50%. Furthermore, the proposed method can be easily implemented for the low complex next generation MIMO-OFDM based WLAN systems.

We consider joint estimation of carrier frequency offset and channel impulse response (CIR) for orthogonal frequency division multiplexing (OFDM) systems with pilot symbols and virtual subcarriers (VCs). We derive the receive-signal correlation structure due to the pilots and VCs, give the evidence of joint multivariate Gaussian distribution of the received samples, and derive an approximate maximum likelihood (ML) frequency offset estimator. We also derive the asymptotic mean-square error (MSE) and an approximate Cramer-Rao bound (CRB) and establish the asymptotic unbiasedness. Without pilots, in high signal-to-noise ratio, our estimator is equivalent to Liu and Tureli's estimator with Nv virtual carriers. When the pilot number (Np) is greater than the channel length L, our estimator acts as a subspace-based estimator with Nv + Np - L virtual carriers. A decision-directed joint ML estimator is derived to iteratively update the estimates of frequency offset, data symbols and CIR. The optimal pilot and virtual carrier placement strategies are also discussed. The resulting decision-directed joint estimator performs within 0.8 dB of the ideal case even when the frequency offset is as large as 20%

This paper presents a new carrier frequency offset (CFO) estimation algorithm with low-complexity for uplink OFDMA systems. Extended Kalman Filter (EKF) is employed in time domain, while the multiple access interference (MAI) cancellation strategy is combined in every recursion. In addition, an adaptive noise variance estimator is contrived for EKF, and a robust EKF method is derived for CFO estimation with data symbols. The proposed algorithm is suitable for online estimation, and can be applied to both preamble and data symbols. Simulation results show that it has a large estimation range, while approaching the Cramer-Rao Bound (CRB) closely with quite reduced complexity.

In this paper, we propose a hybrid scheme for the carrier frequency offset (CFO) estimation in OFDM communication systems. The main novelty of the approach is the judicious combination of two methods so as to reduce the bandwidth overhead and computational complexity without compromising the estimation range. The cyclic prefix (CP) associated with the OFDM symbols are used for the fractional frequency offset estimation. The integer frequency offset is estimated by means of a cost function minimization employing a few null subcarriers, which are allocated using a modified Fibonacci series. Performance of the frequency offset estimator is mathematically analyzed by deriving the Cramer-Rao bound (CRB) and is compared with the mean square error performance of the estimator. For moderate SNRs, our algorithm is shown to outperform some existing methods in terms of MSE (and thereby BER) performance, training overhead and receiver complexity.

We investigate a carrier frequency offset (CFO) estimation algorithm for coherent optical quaternary phase-shift keying (QPSK) receivers. The algorithm utilizes the phase difference between the samples with different time-domain separations, so that the estimation accuracy can be significantly enhanced, compared with the algorithm that only compares the phase difference between adjacent samples. In a 28-GBaud coherent QPSK system, simulation results show that when 16 time spans and 512 samples are utilized, a uniform standard deviation of less than 3 MHz can be achieved for the CFO estimation error, when the optical signal-to-noise ratio is 11.5 dB.

The frequency synchronization issue of multiuser in the uplink of an orthogonal frequency-division multiple-access (OFDMA) system is investigated in this letter. We develop a subspace based blind carrier frequency offsets (CFOs) estimation algorithm for the base station (BS) equipped with uniform linear array (ULA). Due to the adoption of ULA at the BS and the narrowband signal assumption, CFOs of different users can be separated by their spatial information. Thus, unlike existing blind alternatives, which are subject to some specific carrier assignment schemes (CAS) or rely on null subcarriers, our proposed method can support generalized carrier assignment scheme (GCAS) and fully loaded systems, i.e., all subcarriers are available to users. Consequently, the dynamic channel assignment is available and the bandwidth efficiency is higher. Moreover, the closed-form directions of arrival (DOAs) of all active users are also obtained, which can be used in downlink beamforming in frequency division duplex (FDD) systems. Performance of the proposed scheme is evaluated by computer Monte Carlo simulations.

In this literature, we present a new method for estimating the coarse frequency offset in multi-band orthogonal frequency division multiplexing (MB-OFDM) based ultra-wideband (UWB) communication systems. The proposed training based coarse frequency offset (CFO) estimator performs an averaging of initial estimate over the multiple bands of transmission during estimation process. The proposed multi-band averaging provides an improved estimation of approximately three times for band group 1 (BG1) compared to our earlier proposed scheme. To prove the efficiency of the proposed scheme, the Cramer Rao lower bound (CRLB) of the estimation error is calculated and compared with the simulation results. We illustrate the performance of MB-OFDM system in terms of bit-error rate (BER) with multi-band averaged frequency synchronization (MBAFS) and compare with earlier reported results for 100,000 noisy realizations in UWB channel model 2 (CM2).

We evaluate the performance improvement in orthogonal frequency-division multiplex access (OFDMA) achievable with cooperative relaying in the presence of frequency offsets. The relays can operate in either the amplify-and-forward (AF) or decode-and-forward (DF) mode. In each transmission, node S has M relays when transmitting its own signal, and it also helps the other M relays transmit their signals. The total power used to transmit each symbol, including the power consumed in S and the relays, is kept constant. The outage information rates of the proposed cooperative transmission scheme are first derived. The performance improvement in the frequency offset estimation by using cooperative relay is then analyzed. Channel estimation in a cooperative OFDMA network in the presence of frequency offsets is also evaluated, and the pairwise error probability (PEP) of orthogonal space-time coding in cooperative OFDMA due to both the frequency offset and channel estimation errors is derived. Numerical results illustrate the superior performance of the proposed scheme over the conventional transmission with regard to outage information rate, frequency offset estimation error and the PEP.

This paper proposes a high-performance and relatively low-complexity approximated maximum likelihood estimator (MLE) for carrier frequency offset (CFO) in practical orthogonal frequency multiplexing (OFDM) systems, where the preamble has repetition structure in time domain, null subcarriers are allocated at two ends of the frequency spectrum, and the channel impulse response is assumably not longer than the cyclic prefix. We show the optimality of conventional MLEs do not hold in such systems, and derive a universal MLE and its modified Cramer-Rao lower bound in the general case. To reduce the complexity, we propose to cascade it with a low-complexity rough CFO estimator so that only a moderate number of maxima searches are needed to achieve satisfactory performance. Simulation with the IEEE 802.16 preamble symbol confirms the excellent performance of the proposed method.

The paper deals with the problem of the carrier frequency-offset (CFO) estimation for wireless communications. Since the well-known maximum-likelihood (ML) CFO estimator is rather complex, many complexity-reduced CFO estimators have so far been proposed. However, most of them are based on periodic training sequences and have limited estimation range. We propose a general framework called composite frequency- offset estimator (CFE), which can extend the estimation range of any range-limited correlation-based CFO estimator up to the full transmission spectrum. We first formulate the CFO estimation as a problem of composite hypothesis testing, and then solve the problem by the composite hypothesis testing approaches. We show that the composite frequency-offset estimate is the ML estimate as long as the original range-limited estimator is unbiased and attains the Cramer-Rao Lower Bound. The CFE also allows a flexible tradeoff between the estimation range and computational complexity. Finally, numerical results show the efficiency of the proposed method.

This paper presents a complete synchronisation scheme of a baseband OFDM receiver for the currently designed 4G mobile communication system. Since the OFDM transmission is vulnerable to time and frequency offsets, accurate estimation of these parameters is one of the most important tasks of the OFDM receiver. In this paper, the design of a single OFDM synchronisation pilot symbol is introduced. The pilot is used for coarse timing offset and fractional frequency offset estimation. However, it can be applied for fine timing synchronisation and integer frequency offset estimation algorithms as well. A new timing metric that improves the performance of the coarse timing synchronisation is presented. Time domain synchronisation is completed after receiving this single OFDM pilot symbol. During the tracking phase, carrier frequency and sampling frequency offsets are tracked and corrected by means of the nondata-aided algorithm developed by the author. The proposed concept was tested by means of computer simulations, where the OFDM signal was transmitted over a multipath Rayleigh fading channel characterised by the WINNER channel models with Doppler shift and additive white Gaussian noise.

Activity recognition is an important component of pervasive computing applications. Device-free activity recognition has the advantage that it does not have the privacy concern of using cameras and the subjects do not have to carry a device on them. Recently, it has been shown that channel state information (CSI) can be used for device-free activity recognition. Their key limitation lies in the lack of universality. In this paper, we propose ARM, a wireless human Activity Recognition and Monitoring system. ARM investigate the correlation between CSI phase variation and human activity. We present an efficient carrier frequency offset (CFO) estimation algorithm for Wi-Fi devices and introduce Haar wavelet function to eliminate the noises. After these preprocessing, ARM uses the correlation as the profiling mechanism and recognizes a given activity by profile matching. We implemented ARM using both commercial Wi-Fi devices and USRP to evaluate it in different environments. Our result- s show that ARM achieves an average accuracy of greater than 75%.

A novel blind carrier frequency offset (CFO) estimation algorithm was proposed which is based on estimating signal parameter via rotational invariance techniques (ESPRIT) for multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems with virtual carriers. The algorithm estimates CFO in closed-form by jointly exploiting the shift-invariant structure of received signals on multiple receive antennas. It can work effectively in different type of channel. Performance analysis of the proposed algorithm using Monte Carlo simulations and comparisons with some existing approaches are also reported.